The Analytics Lifecycle Toolkit

CHAPTER 4Data Strategy, Platforms, and Architecture

Not having a data strategy is analogous to allowing each person within each department of your organization to develop their own chart of accounts and use their own numbering scheme.

Sid Adelman, Data Warehousing Expert (Adelman, Moss, & Abai, 2005)

Analytics relies on data. While this may seem like an obvious point, it is worth repeating here. Regardless if you are making a decision, solving a problem, investigating a new venture, or considering how to defend against potential threats, you will use facts to help frame the problem, determine its impact, understand the realities, and act as a basis for investigating possible solutions.

How much data is required? Do we need a data warehouse? Should we structure our data in an enterprise data warehouse, data mart, or data lake? Ultimately, many of these questions should be answered by a data strategy and careful alignment of the resources required to meet the aspirational goals of your analytics capability.

In this chapter, a number of these questions will be discussed in the context of a data strategy. Note that I distinguish here between the overall strategy for an analytics organization (discussed in Chapter 3) with data strategy. Data strategy in this context refers to how an organization decides what data they will collect and actively manage. In this chapter, I frame the discussion about data strategy in a similar way that we talk about business strategy—underscoring ...